Planning, both “operational” and
“strategic”, relies on accurate forecasting. Planning in
tourism is no less dependent on accurate forecasts. However, tourism
demand forecasting has been dominated by the application of
regression/econometric techniques. Past studies on the forecasting
accuracy of econometric/regression models suggest that forecasts
generated by these models are not necessarily superior to forecasts
generated by simple time series techniques. Seven time series
forecasting techniques were used to generate forecasts of international
tourist arrivals from Thailand to Hong Kong. The results confirm that
simple techniques may be just as accurate and often more time‐and
cost‐effective than more complex ones. Practitioners in the tourism
industry may confidently use any of the forecasting techniques
demonstrated here for their short‐term planning activities.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.